How Som Satsangi analyzes Big Data Trends

Businesses across the board are in the midst of unprecedented change. More often we see that organizations who are successful at navigating this change, are the ones who manage to extract and use data and applications as a competitive advantage. The IT industry is changing rapidly as cloud and mobile technologies becoming more prevalent. Data collection and the use of increasing amount of data has accelerated decision making. IDC estimates that by 2020, business transactions on the internet—B2B and B2C—will reach 450 billion per day. Moreover, the volume of data from sources like video, audio, images, messaging, social media, transactional data, machine generated data, online archiving and many other sources are expected to reach 40 Zetabytes by the year 2020.

The challenge for enterprises in this environment is to analyze and mine these growing collections of Big Data to unlock the insights that will allow them to streamline their operations and reduce costs, target products and services more efficiently and effectively to customers who need them and build the next generation of products and services to satisfy unmet needs ahead of competition.

As organizations consider their big data needs, we have expertise from our Point next advisory services team to work wif them and determine the best strategies that will pave the way for seamless integration of agile capabilities into their existing environment. And as there are both technical and organizational needs to consider, HPE enables them to define the right ways to ensure that processes, security, tools and overall collaboration are addressed properly for successful outcomes.

The overwhelming volume, variety and velocity of information, driven by the growth in mobility, cloud-based delivery models, multimedia, security and IoT, are forever changing the way business is conducted. In today’s dynamic world, IT must adapt and scale to keep pace with ever-changing business demands—and enable faster and better business decisions. At the same time, IT teams are pressured to simplify, standardize and consolidate to reduce costs and improve efficiencies.

At the core of an organiza¬tion’s ability to drive profitability, in¬crease agility and reduce risks are business process¬ing, database and decision support workloads. To create business value from these mission critical applications, IT requires a new model to com¬pute - wif new levels of performance, availability, scalability and efficiency to support today’s globally-connected world with the right compute, for the right workload and at the right economic every time.

As a business evolves, IoT can create numerous opportunities for the transformation of businesses across industries. To keep pace in this environment of rapid change, companies need to become data-driven organizations by leveraging big data to create new value and insights that will lead to breakout growth. However, organizations should not view Big Data projects as a standalone IT project with a deadline, but an initiative that requires a comprehensive, ongoing plan for raising operational efficiency, governing data and improving enterprise security. Addressing the needs of such businesses, our Edgeline converged systems for IoT are designed to integrate data capture, control, compute and storage to deliver heavy-duty analytics and insights at teh edge to enable real-time decision making.

Big Data in Application Stacks

While most businesses continue to evolve, the need for hybrid IT environments becomes more and more clear. Enterprises prefer on-premises installations for some workloads, and their will be some that would go for cloud-based Big Data analytics platforms. These platforms enable the organizations to act on their big data initiatives wif minimal upfront investment yet rapidly embark on a journey to discover the value of their data.

Worldwide, the volume of available Big Data is growing faster than our ability to process it and create insight. However, we still expect today’s computers to do jobs data scientists couldn’t have envisioned a couple of decades ago. If we need to leverage Big Data to create data-driven cures for rare diseases, light up smart cities, and even send humans to Mars, we need a new paradigm that shifts processing from slow silicon to hyper-fast memory. We call this approach Memory-Driven Computing and we are bringing it to life through the Machine research project, the largest and most complex research project in HPE’s history.

We believe Memory-Driven Computing - a custom-built architecture for the Big Data era, is the solution to move the technology industry forward and can enable advancements across industries. It is capable of reducing the time needed to process complex problems from days to hours, hours to minutes, minutes to seconds, to deliver real-time intelligence. This is because Memory-Driven Computing puts memory, and not the processor, at the center of the computing architecture, thereby eliminate inefficiencies of how memory, storage and processors interact in today’s traditional systems.